ARF: A hybrid model for credit scoring in complex systems

作者：

Highlights：

• A hybrid model for credit scoring in complex systems.

• Using stock market data and expert opinions to identify changes in economic patterns.

• Using stock market data to identify the economic situation of different markets.

• Applying ANFIS and RNN models to identify the economic pattern of the market.

• Development of a hybrid model of quantitative (previous data) and qualitative (expert opinion) and fuzzy rule base.

摘要

•A hybrid model for credit scoring in complex systems.•Using stock market data and expert opinions to identify changes in economic patterns.•Using stock market data to identify the economic situation of different markets.•Applying ANFIS and RNN models to identify the economic pattern of the market.•Development of a hybrid model of quantitative (previous data) and qualitative (expert opinion) and fuzzy rule base.

论文关键词：Stock market forecast,Adaptive neuro-fuzzy inference systems,Recurrent neural network,Fuzzy rule base,Credit scoring,Economic shocks

论文评审过程：Received 12 November 2020, Revised 17 May 2021, Accepted 18 July 2021, Available online 23 July 2021, Version of Record 26 July 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115634